Field of the Invention
The specification generally relates to providing a user interface for guiding the user to capture a series of images to create a single linear panoramic image. In particular, the specification relates to a system and method for generating one or more user interface elements that provide instantaneous feedback to guide the user in capturing the series of images to create the single linear panoramic image. More particularly, the specification relates to camera pose yaw error determination and use of the error in a user interface.
Description of the Background Art
A planogram is a visual representation of products in a retail environment. For example, a planogram may describe where in the retail environment and in what quantity products should be located. Such planograms are known to be effective tools for increasing sales, managing inventory and otherwise ensuring that the desired quantity and sizes of an item are placed to optimize profits or other parameters. However, presentation and maintenance of adequate levels of stock on shelves, racks and display stands is a labor-intensive effort, thereby making enforcement of planograms difficult. While the location and quantity of products in retail stores can be manually tracked by a user, attempts are being made to automatically recognize the products and automatically or semi-automatically obtain information about the state of products.
When an image is captured for a planogram, if a tilt error is present in the image, distortion will be introduced into the planogram. Most systems do not include internal accelerometers to detect a yaw error tilt. Furthermore, previous attempts at using existing internal accelerometers to detect a yaw error tilt in a captured image have been unsuccessful. For every angle of yaw rotation, internal accelerometers report the same value, resulting in images for planograms with yaw error rotation.
Previous attempts at recognizing products have deficiencies. For example, one method to achieve the goal of recognizing multiple products from multiple images is through image stitching. Unfortunately, existing image stitching techniques can lead to artifacts and can interfere with the optimal operation of recognition.